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Inka Milewski Conservation Council of New Brunswick

Identifying at-risk communities for action on cancer prevention: a case study in New Brunswick (Canada) communities. Inka Milewski Conservation Council of New Brunswick CRDCN 2012 National Conference: Evidence-based Policy Formation and Evaluation Fredericton, New Brunswick

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Inka Milewski Conservation Council of New Brunswick

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  1. Identifying at-risk communities for action on cancer prevention: a case study in New Brunswick (Canada) communities InkaMilewski Conservation Council of New Brunswick CRDCN 2012 National Conference: Evidence-based Policy Formation and Evaluation Fredericton, New Brunswick October 23, 2012

  2. What do we know about cancer rates in Canadian communities? • Guernsey et al 2000 • Sydney, Nova Scotia • higher rates of breast and cervical cancer than provincial rates • higher rate of colon, rectum and prostate cancer among men than provincial rates • Holowaty et al. 2010 - Ontario public health unit (Wellington-Dufferin-Guelph) - highest rate of lung cancer in urban core area of Guelph - highest rate of prostate cancer in the Orangeville area • Colquhoun et al. 2010 • First Nations community of Fort Chipewyan, Alberta • higher rates of cervical and biliary tract, other and unspecified cancers than all First Nations in Alberta and Alberta general population

  3. Study Design • 9 rural and 5 urban communities • 6 primary cancers for males (prostate, lung, colorectal, bladder, NHL, kidney) • 4 primary cancers for females (breast, lung, colorectal, NHL) • age-unadjusted cancer incidence rates per 100,000 population (1989-2005) with 95%Cl • Community SES measures (education, poverty rate, income, unemployment)

  4. Statistical Analysis • Multivariate ordination (MDS) to plot similarities in cancer incidence among communities • Hierarchical cluster analysis to identify possible clusters and permutation testing (SIMPROF) to test the significance of clusters • Permutation testing (RELATE) to test the correlation of SES pattern and cancer incidence

  5. 2D Stress: 0.05 2D Stress: 0.04 Upper Miramichi Fredericton Harvey Edmundston Minto Gagetown Saint John Bathurst Drummond- Denmark Moncton Gagetown Miramichi Dalhousie Dalhousie Bathurst Caraquet Edmundston Moncton Harvey Miramichi Fredericton Caraquet Saint John Drummond- Denmark Upper Miramichi Belledune Belledune Minto Non-metric multidimensional scaling (MDS) plot of similarities in male and female age unadjusted cancer incidence rates among 5 urban (■) and 9 rural (▼) communities Females Males p < 0.001 p < 0.001

  6. MDS plot of similarities in socioeconomic status (SES) among among 5 urban (■) and 9 rural (▼) communities New Brunswick communities

  7. Correlation between cancer rates and SES factors ρ = - 0.071 males ρ = 0.041 females

  8. Age-standardized vs age-unadjusted Cancer Rates Milewski and Liu 2009

  9. Milewski and Liu 2009

  10. Milewski and Liu 2009

  11. Conclusions • Rates of cancer differed significantly among New Brunswick communities and were unrelated to SES • Reporting data at the right spatial scale is key to avoiding policy mismatches • Identifying at-risk communities can result in the development of more appropriate risk reduction and prevention programs

  12. Acknowledgments • Lilly Liu, CCNB research assistant • EJLB Foundation • Salamander Foundation • New Brunswick Cancer Network • Statistics Canada

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